Design, build, and operationalise large-scale cloud data pipelines (batch and streaming) using Databricks/Snowflake and cloud platforms to support reporting, automated systems and AI/ML teams. Administer cloud data platforms, optimise SQL/storage, implement CI/CD, IaC, containerisation and serverless solutions, and collaborate with clients, partners and internal teams to scale data engineering deployments.
Temus is a Temasek-backed consulting firm providing digital transformation solutions for the private and public sectors. We aspire to be a strategic partner in realising the Singapore Government’s Smart Nation vision. We are headquartered in Singapore and have more than 400 employees across a wide range of disciplines in strategy, design, architecture, technology, data & AI.
Title: Data Engineer
Your Objectives
- Place client value and human experience at the center of everything we do.
- Develop and deliver value to clients by building large scale enterprise data pipelines to capture, transform and store data to support reporting, automated systems and AI/ML teams.
- Be a part of a world-class team of experts in data engineering.
- Be a part of a culture of excellence and with confidence, charisma, context, and humility, working effectively at all levels.
Delivery
- Delivery of data pipelines to drive material impact and drive disruptive transformation across our clients in public and private sectors.
- Support thought leadership development as a team for data engineering and scaling deployments.
Partnership
- Work with Temus' ecosystem of partners to deliver client value.
- Adopt a cloud-first strategy to enhance agility and elasticity by partnering with vendors to support specific public sector needs.
Requirements
- Minimum 3–5 years of designing, building and operationalising data solutions and applications (with batch or streaming data).
- Hands-on experience with Databricks/Snowflake including setup, configuration, administration on cloud infrastructure followed by on-boarding data sources, building data pipelines and data assets for downstream consumption.
- At least 3 years of experience with cloud data platforms on AWS (S3, RDS, Glue, Redshift), GCP (BigQuery, Bigtable, Dataflow, Cloud Storage), or Azure (Synapse Analytics, Azure Data Factory, Azure Data Lake Storage, Cosmos DB).
- Proficient in at least one core language: Python, .Net (C#).
- Experience with setup and administration of Tableau server is an added advantage.
- Knowledge of Kafka for data streaming (producer, topics and consumers).
- Excellent understanding of SQL data storage structures and storage/query optimisations.
- Mastered SQL querying to build any data presentations using joins, reference tables, groupings, statistics etc.
- At least 3 years of implementation experience with serverless computing, CI/CD, containerisation, Infrastructure as Code (IaC), code version control and automated testing.
- Strong ability to communicate with a broad range of clients, colleagues, and partners across a variety of contexts and formats.
- Strong ability to develop and maintain relationships amongst clients, colleagues, and partners.
- Show active tracks of improving knowledge and skills (e.g. courses, podcasts, books, experimentation, open source volunteering, tech meetups etc.).
- Familiarity with agentic coding tools such as Claude Code, Cursor and Google Antigravity will be an advantage.
- Ability to work independently with minimal guidance.
- Ability to work as part of a large team.
- Ability to work within an unstructured environment with ability to multitask well.
Temus is an equal opportunities employer. We welcome applications from all. We do not discriminate by race, religion, belief, ethnicity, origin, disability, age, partnership status, sexual orientation, or gender identity.
We see the diversity of our team as a strategic advantage, and we work actively to maintain it.
By applying for this role, you have read and acknowledge the data privacy statement via this link - temus.com/job-applicant-data-protection/
Temus Singapore, Singapore, SGP Office
Mapletree Business City, 80 Pasir Panjang Road, 22-81, Singapore, Singapore, 117372
Similar Jobs
.jpeg)
Artificial Intelligence • Hardware • Information Technology • Machine Learning
Develop and deploy product-disposition workflows and deviation alert systems using statistical tools and ML/AI to improve yield, reliability, and quality. Build algorithms for data mining, pattern recognition, and wafer/die screening. Collaborate with Fab, design, and quality teams, mentor team members, and drive technical innovation to meet KPIs like quality, cost, cycle time, and scale.
Top Skills:
AIData MiningDeep LearningJmpMachine LearningPower BITableau
Artificial Intelligence • Hardware • Information Technology • Machine Learning
Design, build, and productionize GenAI and ML solutions for semiconductor engineering: large-scale data pipelines, LLM/RAG and agentic workflows, model training/inference, analytics, deployment, monitoring, and cross-functional collaboration to improve quality, cost, and engineering productivity.
Top Skills:
AgentevalAutogenAWSAzureBigQueryClaude CodeClineCursorGCPGemini CliGoogle AdkLanggraphLlmsMatplotlibPandasPlotlyPysparkPythonPyTorchRagRoo CodeScikit-LearnSQLTensorFlowWindsurf
Artificial Intelligence • Hardware • Information Technology • Machine Learning
Responsible for building and maintaining data pipelines, optimizing data structures, and developing ETL processes with AI support for data analytics applications.
Top Skills:
Apache Ni-FiC#C++Ci/CdData EngineeringDockerETLGitGoogle Cloud PlatformHadoopJavaJenkinsKubernetesNoSQLPythonSnowflakeSQL
What you need to know about the Singapore Tech Scene
The digital revolution has driven a constant demand for tech professionals across industries like software development, data analytics and cybersecurity. In Singapore, one of the largest cities in Southeast Asia, the demand for tech talent is so high that the government continues to invest millions into programs designed to develop a talent pipeline directly from universities while also scaling efforts in pre-employment training and mid-career upskilling to expand and elevate its workforce.
